journal article·2023-02-09Open access

A Systematic Literature Review on Urban Resilience Enabled with Asset and Disaster Risk Management Approaches and GIS-Based Decision Support Tools

Seyed MHS Rezvani, Maria João Falcão, Dragan Komljenovic, Nuno Marques de Almeida

Applied Sciences· Volume 13· Issue 4

Abstract

Urban Resilience (UR) enables cities and communities to optimally withstand disruptions and recover to their pre-disruption state. There is an increasing number of interdisciplinary studies focusing on conceptual frameworks and/or tools seeking to enable more efficient decision-making processes that lead to higher levels of UR. This paper presents a systematic review of 68 Scopus-indexed journal papers published between 2011 and 2022 that focus on UR. The papers covered in this study fit three categories: literature reviews, conceptual models, and analytical models. The results of the review show that the major areas of discussion in UR publications include climate change, disaster risk assessment and management, Geographic Information Systems (GIS), urban and transportation infrastructure, decision making and disaster management, community and disaster resilience, and green infrastructure and sustainable development. The main research gaps identified include: a lack of a common resilience definition and multidisciplinary analysis, a need for a unified scalable and adoptable UR model, margin for an increased application of GIS-based multidimensional tools, stochastic analysis of virtual cities, and scenario simulations to support decision making processes. The systematic literature review undertaken in this paper suggests that these identified gaps can be addressed with the aid of asset and disaster risk management methods combined with GIS-based decision-making tools towards significantly improving UR.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Flood Risk Assessment and Management · Disaster Management and Resilience · Infrastructure Resilience and Vulnerability Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal

Laboratório Nacional de Engenharia Civil, Av. do Brasil 101, 1700-075 Lisboa, Portugal

Institut de Recherche d’Hydro-Québec (IREQ), 1800, Boul. Lionel-Boulet, Varennes, QC J3X 1S1, Canada

Funding

Fundação para a Ciência e Tecnologia

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